Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/31163

TitleAn assessment on the length of hospital stay through Artificial Neural Networks
Author(s)Abelha, Vasco António Pinheiro Costa
Vicente, Henrique
Machado, José Manuel
Neves, José
KeywordsHealthcare
Length of hospital stay
Logic programming
Knowledge representation and reasoning
Artificial Neuronal Networks
Issue date2014
PublisherSpringer
Abstract(s)The attitude of stashing costs and preventing people of any kind of intervention on the valuation of the problem referred to above, may undermine their belief on present society values and on their way of living. Cutting funds from Education to Health is at best delaying the inevitable crash that is foresha- dowed. Indeed, regarding people, a major concern may be described as jeopar- dizing their health condition, i.e., providing healthcare is a very sensitive issue and prunes to drastic changes in short spaces of time. Factors like age, sex, and context – house conditions, daily lives – should also be central when deciding how long a specific patient should remain in a hospital. In no way, ought this be decided by economic circumstances alone. To fulfill this goal, a Logic Pro- gramming based approach is used for knowledge representation and reasoning, letting the modeling of the universe of discourse in terms of defective data, in- formation and knowledge. Artificial Neural Networks are enforced as the com- putational framework, allowing one to predict how long a patient should remain in a hospital.
TypeConference paper
URIhttp://hdl.handle.net/1822/31163
Peer-Reviewedyes
AccessRestricted access (UMinho)
Appears in Collections:CCTC - Artigos em atas de conferências internacionais (texto completo)

Files in This Item:
File Description SizeFormat 
paperKicss.pdf
  Restricted access
524,09 kBAdobe PDFView/Open

Partilhe no FacebookPartilhe no TwitterPartilhe no DeliciousPartilhe no LinkedInPartilhe no DiggAdicionar ao Google BookmarksPartilhe no MySpacePartilhe no Orkut
Exporte no formato BibTex mendeley Exporte no formato Endnote Adicione ao seu ORCID